Modern portable consumer and industrial electronics, especially client devices such as cellular phones, portable digital assistants, navigation systems, and combination devices, are providing increasing levels of functionality to support modern life including mobile data and voice services. Research and development in the existing technologies can take a myriad of different directions.
As users become more empowered with the growth of mobile service devices, new and old paradigms of cellular service stations are becoming essential for users to take advantage of this new mobile data and voice space. Base stations can provide mobile data and voice services. Base stations allow a Mobile Station, such as a User Equipment, to connect to its voice or data services remotely via radio frequency communication. Noise ratio calculation mechanisms help the mobile stations and the base stations manage the communication channel and properly decode symbols transmitted over the radio frequency.
Mobile telecommunication systems have been incorporated in cellphones, handheld devices, automobiles, notebooks, and other portable products. Today, these systems aid users by decoding audio and multimedia data over portable devices and manage the radio frequency communication between the user equipment and the nearby servicing base stations. The proper noise ratio estimation prevents interruption of services because of delay, noise, or interference within the communication channels. However, the accuracy and consistency of these noise ratio estimation mechanisms continue to challenge commercial applicability of these systems.
Thus, a need still remains for a mobile telecommunication system with a noise ratio estimation mechanism to adjust telecommunication receiver for better throughput. In view of the ever-increasing commercial competitive pressures, along with growing consumer expectations and the diminishing opportunities for meaningful product differentiation in the marketplace, it is increasingly critical that answers be found to these problems. Additionally, the need to reduce costs, improve efficiencies and performance, and meet competitive pressures adds an even greater urgency to the critical necessity for finding answers to these problems.
Solutions to these problems have been long sought but prior developments have not taught or suggested any solutions and, thus, solutions to these problems have long eluded those skilled in the art.